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Min-Max-Normalisering×Multi-Attributive Border Approximation area Comparison×
ÄmnesområdeBeslutsfattandeBeslutsfattande
FamiljMCDMMCDM
Ursprungsår19812015
UpphovspersonHwang, C. L., Yoon, K.Pamučar, D., Ćirović, G.
TypNormalization (linear, range-scaling)Border approximation area (distance from BAA)
UrsprungskällaHwang, C. L., Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Lecture Notes in Economics and Mathematical Systems, Vol. 186, Springer-Verlag DOI ↗Pamučar, D., Ćirović, G. (2015). The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC). Expert Systems with Applications DOI ↗
Alias
Närliggande88
SammanfattningMIN-MAX-NORMALIZATION (Min-Max Normalization — linear rescaling of each criterion column to [0, 1]) is a normalization multi-criteria decision-making (MCDM) method introduced by Hwang, C. L., Yoon, K. in 1981. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.MABAC (Multi-Attributive Border Approximation area Comparison) is a ranking multi-criteria decision-making (MCDM) method introduced by Pamučar, D., Ćirović, G. in 2015. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result.
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ScholarGateJämför metoder: MIN-MAX-NORMALIZATION · MABAC. Hämtad 2026-06-17 från https://scholargate.app/sv/compare